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Variable location and scale kernel density estimation
Authors:M. C. Jones  I. J. McKay  T. -C. Hu
Affiliation:(1) Department of Statistics, The Open University, MK7 6AA Milton Keynes, U.K.;(2) Department of Statistics, University of British Columbia, 2021 West Mall, V6T 1W5 Vancouver, Canada;(3) Department of Mathematics, National Tsing Hua University, Hsinchu, Taiwan 30043, R.O.C.
Abstract:Variable (bandwidth) kernel density estimation (Abramson (1982,Ann. Statist.,10, 1217–1223)) and a kernel estimator with varying locations (Samiuddin and El-Sayyad (1990,Biometrika,77, 865–874)) are complementary ideas which essentially both afford bias of orderh4 as the overall smoothing parameterh rarr 0, sufficient differentiability of the density permitting. These ideas are put in a more general framework in this paper. This enables us to describe a variety of ways in which scale and location variation may be extended and/or combined to good theoretical effect. This particularly includes extending the basic ideas to provide new kernel estimators with bias of orderh6. Technical difficulties associated with potentially overly large variations are fully accounted for in our theory.
Keywords:Bias reduction  smoothing  variable bandwidth
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